OEE – how to measure the ultimate KPI
25 June 2008
A measurement of Overall Equipment Effectiveness (OEE) is increasingly used to quantify the efficiency of manufacturing processes, but gathering the required information to make the calculation is challenging.
The difference between 500 and 600 items a minute can be the difference between profit and loss
Tony Chapman, of Siemens Automation and Drives, explains the thinking behind OEE and offers a possible solution to data collection issues.
Increasingly stringent quality requirements coupled with rapid product changes and frequent modifications are making production processes ever more complex. In tandem, other factors, such as fluctuating plant utilisation and unavoidable quality differences in deliveries can negatively impact system productivity.
An ability to find why a machine is producing 500 items, not 600, per minute could mean the difference between profit and loss. So manufacturers want answers to key questions. What is my actual performance as measured against my performance targets? How effective are we at utilising our resources? Why is one of my lines idle or unproductive? Are our resources utilised efficiently for the products being made? Why do two seemingly equal production teams make products that differ massively in terms of quality?
The answers allow the production manager to make the correct business decisions in terms of investment in new plant or increasing the throughput of the existing assets.
Plant operation data can be used to calculate OEE, which is a metric defined by the Japanese Institute of Plant Maintenance. OEE is an accepted Key Performance Indicator (KPI) for plant / machine effectiveness. One of the major goals of an OEE program is to reduce and/or eliminate what are regularly referred to as the Six Big Losses – the most common causes of efficiency loss in manufacturing. These are:
* Breakdown and downtime losses
* Set-up losses
* Minor stops
* Reduced speed losses
* Big losses including start-up rejects and quality losses, rejecting parts during the start-up phase of a machine
* Production rejects and rework quality losses
The simple OEE calculation is: OEE = Availability x Performance x Quality
Eliminating the six big losses can help take productivity from average to good and from good to great, but finding the causes can only be achieved by recording machine and operating data which forms the basis for optimum information quality and decision-making.
SCADA systems are an excellent way of quickly collecting and analysing data and can easily be equipped with an extra downtime analysis tool to calculate and distribute OEE data.
With downtime analysis, the time model of the production equipment is determined from the production times, maintenance times and downtimes. Via a shift calendar, the shifts can also be included in the analysis. All plant statuses, relevant for the analysis, are parameterised in a detailed reason tree. The acquired data provides information about the efficiency of individual machines and entire production plants. The transparency of the data makes it possible to quickly respond to malfunctions and to take corrective measures, which again increases the machine availability.
Sophisticated software tools are needed to calculate and analyse OEE data. Adding downtime analysis to an existing SCADA system allows the end user to detect which plant components make what contribution to the OEE, and where the weak points are that have a negative impact on the OEE. This information helps maintenance personnel decide which measures will have the maximum short-term effect, and enables operations scheduling to allocate job orders to specific lines or subsystems.
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